基于期望轨迹补偿的机器人鲁棒自适应控制

Robust Adaptive Controller for Robot Manipulator Based on Desired Trajectory Compensation

针对机器人存在的参数不确定性和外扰的问题,提出了一种基于期望轨迹补偿和自适应控制的方法,在传统自适应控制方法的基础上,结合变结构控制方法,设计了一种新的控制策略。该方法采用期望轨迹补偿,离线计算回归矩阵,可以有效节约控制系统在线计算的时间,实时性好,并利用变结构思想补偿非线性摩擦和外界干扰,利用lyapunov直接法分析证明系统可实现全局渐进稳定,而且由于自适应率中不含有不确定项,可以有效解决参数辨识过程中的参数漂移问题,仿真结果也表明,系统估计参数收敛于真实值,并对于系统不确定性和外扰具有较好的鲁棒性。

A robust adaptive controller with guaranteed transient performance under a desired compensation adaptation law is developed for trajectory tracking control of robot manipulator in the presence of parametric uncertainties and external disturbances. With some modifications to the conventional adaptation law, a new control law is redesigned by combining the design methodologies of adaptive control and sliding mode control. The adaptive scheme has best computationally efficient for real-time calculating of the regressor, and compensate nonlinear friction and external disturbances via thought of variable structure. The global asymptotic stability is validated by Lyapunov direct method. Because the adaptation law is robust to uncertainty, the parameter is not contaminated with noise, simulation results show the estimated parameters are converged and the good robust and accuracy ate obtained.